A model to forecast airport-level General Aviation demand |
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| Institution: | 1. Department of Chemical Engineering, Tsinghua University, Beijing 100084, PR China;2. Petroleum Company Ltd., China National Aviation Fuel Group, Beijing 100088, PR China;3. International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria;4. School of Business, East China University of Science and Technology, Meilong Road 130, Shanghai 200237, PR China;1. National Secretariat of Civil Aviation, Ministry of Infrastructure, Brasilia, Brazil;2. Executive Secretariat, Ministry of Infrastructure, Brasilia, Brazil;1. VU University, Amsterdam, The Netherlands;2. SEO Economic Research, Amsterdam, The Netherlands;3. Airneth, The Netherlands;1. University of Jyväskylä, School of Business and Economics, P.O. Box 35, 40014 University of Jyväskylä, Finland;2. University of Jyväskylä, School of Resource Wisdom, P.O. Box 35, 40014 University of Jyväskylä, Finland;3. Griffith University, School of Engineering and Built Environment, 170 Kessels Road, Nathan, Queensland 4111, Australia;4. Griffith University, Cities Research Institute, 170 Kessels Road, Nathan, Queensland 4111, Australia |
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| Abstract: | General Aviation (GA) demand forecast plays an important role in aviation management, planning and policy making. The objective of this paper is to develop an airport-level GA demand forecast model. The GA demand at an airport is modeled as a function of social-economic and demographic factors, the availability of supply factors, the competition from the commercial aviation, the number of based aircraft, and the presence of a flight school. Our models suggest that the relative fuel price – fuel price compared with personal income – is a significant determinant of airport level GA demand. The elasticity of itinerant and local GA demand with respect to the relative fuel price is −0.43 and −0.52, respectively. Our results are compared with those reported in other studies. Furthermore, we made projections of GA demand for the airports in the Terminal Area Forecast (TAF) using three fuel price scenarios from the Energy Information Administration. Our projections under the “business-as-usual” fuel price scenario are close to those in the TAF. Our models could prove useful, for example, for the Federal Aviation Administration and airport planners to prepare airport-level GA demand forecast. |
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| Keywords: | General Aviation Airport-level GA demand forecast Itinerant operations Local operations Relative fuel price Impact of fuel price |
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